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Quantitative Ultrasound Stochastic Tomography - Revolutionizing breast cancer diagnosis and screening with supercomputing-based radiation-free imaging.

Project description

Innovative algorithms revolutionise ultrasound breast cancer imaging

Algorithms developed in the field of geophysical imaging can be used to enhance information from ultrasound imaging in medical applications. The adjoint-state modelling and iterative optimisation will provide quantitative images of human tissue with very high resolution. The EU-funded QUSTom project will investigate the possibility to apply the fundamental science behind adjoint-based uncertainty imaging for breast cancer diagnosis. This feasibility study of the technology as a diagnostic tool will cover the adaptation of data acquisition hardware for optimal resolution, application of the algorithms in high-performance computers, and final feasibility analysis by radiologists as a comparison with the current state-of-the-art imaging in breast cancer diagnostic.

Objective

Ultrasound imaging can be deeply enhanced by means of algorithms developed in the field of geophysical imaging. Such algorithms, based upon adjoint-state modelling and iterative optimization, provide quantitative images of human tissue with very high resolution. At present time, such images can only be attained by means of high-performance computing and using specific ultrasound data acquisition devices. When combined, hardware and software have a huge impact potential for soft-tissue imaging, such as in breast cancer imaging. Nevertheless, and as is customary in medical imaging, the obtained images only provide with the mean, or most likely, values of tissue at each pixel, being uncertainty quantification an extremely expensive process, typically deemed as unfeasible for practical purposes.

A revolutionary development in adjoint-based ultrasound imaging allows us to potentially obtain images of uncertainties at the cost of a single, mean-value, image. Such development will be the basis of transformative implications in terms of confidence-estimates for diagnosis. We aim at disrupting the breast cancer screening paradigm by means of a safe (radiation-free), accurate (quantitative) and reliable (uncertainty-aware) novel breast imaging modality.

Within QUSTom we will investigate the fundamental science behind adjoint-based uncertainty imaging and establish its potential suitability for breast cancer diagnosis. The feasibility of the technology as a diagnosis tool relies on 1) adapting the data acquisition hardware for optimal resolution, 2) implementing the algorithms in high-performance computers in order to obtain a short time-to-solution and 3) feasibility analysis by expert radiologists in comparison with the state-of-the-art in breast imaging.

This proposal covers the three aspects and opens the possibility of applying similar principles in other imaging fields, both in medicine and elsewhere.

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HORIZON-EIC - HORIZON EIC Grants

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Call for proposal

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(opens in new window) HORIZON-EIC-2021-PATHFINDEROPEN-01

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Coordinator

BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 737 303,75
Address
CALLE JORDI GIRONA 31
08034 BARCELONA
Spain

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Region
Este Cataluña Barcelona
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 737 303,75

Participants (4)

Partners (1)

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